Embracing Distributed Acoustic Sensing in Car Cabin for Children Presence Detection

Author:

Su Yuqi1ORCID,Zhang Fusang2ORCID,Niu Kai3ORCID,Wang Tianben4ORCID,Jin Beihong1ORCID,Wang Zhi2ORCID,Jiang Yalan5ORCID,Zhang Daqing6ORCID,Qiu Lili7ORCID,Xiong Jie8ORCID

Affiliation:

1. Institute of Software, Chinese Academy of Sciences; University of Chinese Academy of Sciences, Beijing, China

2. State Key Laboratory of Computer Sciences, Institute of Software, Chinese Academy of Sciences; University of Chinese Academy of Sciences, Beijing, China

3. Peking University; Beijing Xiaomi Mobile Software Company Ltd., Beijing, China

4. College of Mechanical and Electronic Engineering, Northwest A & F University, Yangling, Shaanxi, China

5. Beijing Xiaomi Mobile Software Company Ltd., Beijing, China

6. Telecom SudParis, Institut Polytechnique de Paris, Evry, France; School of Computer Science, Peking University, Beijing, China

7. Microsoft Research Asia, Shanghai, China

8. University of Massachusetts Amherst, Amherst, Massachusetts; United States Microsoft Research Asia, Shanghai, China

Abstract

Contactless acoustic sensing has been actively exploited in the past few years to enable a large range of applications, ranging from fine-grained vital sign monitoring to coarse-grained human tracking. However, existing acoustic sensing systems mainly work on smartphone or smart speaker platforms. In this paper, we envision an exciting new acoustic sensing platform, i.e., car cabin which is inherently embedded with a large number of speakers and microphones. We propose the new concept of distributed acoustic sensing and develop novel designs leveraging the unique characteristics of rich multi-path in car cabin to enable fine-grained sensing even when the primary reflection is totally blocked. By using child presence detection as the application example, we show that child presence can be detected through body motions or even subtle breath (when the child is sleeping or in coma) at all locations in the cabin without any blind spots. We further show that the proposed system can robustly work in different car cabins, achieving an average detection accuracy of 97% and a false alarm rate always below 2% under different scenarios including those challenging ones such as rear-facing seat blockage. We believe the proposed distributed sensing modality in car cabin pushes acoustic sensing one big step towards real-life adoption.

Funder

Beijing Natural Science Foundation

National Natural Science Foundation of China

National Natural Science Foundation of China A3 Foresight Program

Youth Innovation Promotion Association, Chinese Academy of Sciences

Beijing Nova Program

Publisher

Association for Computing Machinery (ACM)

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